How to Use the Vultr MCP in CrewAI

Run autonomous cloud operations on Vultr by coordinating specialized agents with CrewAI.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Vultr MCP to CrewAI

Create your Vinkius account to connect Vultr to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Vultr with CrewAI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Autonomous Resource Discovery

The Research Agent can discover all available resources. It runs `list_bare_metals` and passes the full list to shared memory. Another agent can then run `list_applications`, gathering comprehensive inventory data for analysis. This allows your crew of agents to operate with a single, shared source of truth about your entire Vultr footprint.

Security Credential Management

Assign the Security Agent this task. It can audit access by running `list_api_keys` and then provision new credentials using `create_api_key`. The agent ensures that every action is logged and tracked in the shared memory for compliance. It’s a controlled, role-based process where one specialist handles credential creation while others monitor it.

Complex Network Configuration

The Action Agent manages network changes. It can first check account BGP status with `get_account_bgp`, and then execute a full setup using `setup_bgp`. This task requires multiple data points to succeed. If the primary agent confirms success, a secondary agent can follow up by listing all IP addresses to confirm the change was logged.

Setup guide

Set up Vultr MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Vultr tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Vultr Analyst",
    goal="Access and analyze Vultr data via MCP.",
    backstory="Expert analyst with direct Vultr access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Vultr transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Vultr Analyst",
        goal="Access and analyze Vultr data via MCP.",
        backstory="Expert analyst with direct Vultr access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Vultr transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Vultr. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Vultr now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Vultr MCP in CrewAI

CrewAI assigns specialized roles. One agent researches (e.g., running `list_bare_metals`), and a second agent acts on that data (e.g., calling `halt_bare_metal`). The shared memory facilitates this handoff.

This MCP Server manages bare metal instances, network configurations (IPv4/IPv6), API keys, and backup metadata. All infrastructure state is visible to the agents.

Yes. You can set up a dedicated monitoring agent that periodically calls tools like `list_bare_metals` or `get_account` and reports any deviations from the expected state.

The server touches account information, API keys, bare metal instance status, IP addresses, and backup records. All this core infrastructure data is visible to your agent.

You structure the workflow hierarchically: one agent confirms prerequisites (e.g., `get_account`), and a master agent then executes the core action (e.g., `start_bare_metal`).

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript